Salesforce Com, Inc.

Kavya Murali

Na Cheng

Sitaram Asur

Neeraj Ahuja

Nicholas Beng Tek Geh

Roojuta Lalani

Yixin Mao

Gary Brandeleer

Tyler Shopshire

Sudhakara Reddy Peddi

A system and related processing methodologies for recommending a product based on a work order are described. The system receives an input case description, including a current repair item and a current work type. Historical work orders associating a plurality of products with repair items and work types are searched for a co-occurrence of the repair item matching the current repair item, and the work type matching the current work type. Upon finding a match, the product associated with the match is added to a set of candidate products for the current work order. A similarity measure between the candidate product and current work order description, a current work type category, and popularity of the candidate product is generated and then used in the generation of a probability score for the candidate product and current work order. If the probability score meets a threshold, the candidate product is recommended.

Techniques and architectures for recommending products based on work orders

A method for technical field service inventory management has been developed. A software platform manages product inventory for use by a field service technician. The platform creates objects for a work order, a product required, a location, an address/appointment, a product item, a product item transaction and a product item consumed. The product item consumed object is used to automatically update the status of product inventory as the product is used by the field service technician.

Technical field service inventory management

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Foster City, CA, United States of America

Kavya Murali